AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 129 · 40 questions

AI tip (Fair data, fairer AI): Bias usually comes from the training data: if a group is missing or shown in only one way, the model copies that. One-sided data: one age group, only ripe mangoes, only adult voices, only neat handwriting. Balanced data: many ages, colours, voices, regions and styles. Reduce bias: add varied examples, check who is missing, test on many groups, fix wrong labels and listen to complaints.

1. 1.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
2. 2.True or false: “ignore complaints” adds to bias. (a) True (b) False
3. 3.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) the phone was new (c) it was a rainy day (d) few child voices in data
4. 4.Which of these adds to bias? (a) add varied examples (b) check who is missing (c) fix wrong labels (d) skip testing
5. 5.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
6. 6.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
7. 7.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
8. 8.Which of these adds to bias? (a) ask different people (b) balance the data (c) add varied examples (d) copy old unfair choices
9. 9.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
10. 10.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
11. 11.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
12. 12.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its screen size (c) its colour (d) its training data
13. 13.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a fair model (c) a strong battery (d) bias from data
14. 14.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
15. 15.Which of these helps reduce bias? (a) ignore complaints (b) add more of the same (c) use one group only (d) check who is missing
16. 16.🔍 Which is the odd one out? (a) test on many groups (b) check who is missing (c) ask different people (d) test on one group only
17. 17.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
18. 18.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
19. 19.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
20. 20.🔍 Which is the odd one out? (a) balance the data (b) ask different people (c) add varied examples (d) use one group only
21. 21.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
22. 22.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
23. 23.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
24. 24.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) True (b) False
25. 25.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
26. 26.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
27. 27.Which of these helps reduce bias? (a) balance the data (b) use one group only (c) ignore complaints (d) copy old unfair choices
28. 28.🔍 Which is the odd one out? (a) test on many groups (b) balance the data (c) fix wrong labels (d) copy old unfair choices
29. 29.True or false: “balance the data” adds to bias. (a) True (b) False
30. 30.Which of these helps reduce bias? (a) fix wrong labels (b) add more of the same (c) use one group only (d) ignore complaints
31. 31.True or false: “use one group only” adds to bias. (a) True (b) False
32. 32.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) False (b) True
33. 33.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
34. 34.Which of these helps reduce bias? (a) use one group only (b) copy old unfair choices (c) ignore complaints (d) ask different people
35. 35.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
36. 36.🛠️ What helps make an AI system fairer? (a) fewer tests (b) one group only (c) ignoring mistakes (d) more varied data
37. 37.True or false: “test on many groups” helps reduce bias. (a) False (b) True
38. 38.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
39. 39.🔍 Which is the odd one out? (a) add more of the same (b) skip testing (c) use one group only (d) ask different people
40. 40.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) False (b) True

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